Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers

Therapeutic strategies for adrenocortical carcinoma: integrating genomic insights, molecular targeting, and immunotherapy

Adrenocortical carcinoma (ACC) is an uncommon and highly aggressive cancer originating in the adrenal cortex, characterized by a high likelihood of recurrence and unfavorable survival rates, particularly in the advanced disease stages. This review discusses the complex molecular pathogenesis of ACC, focusing on critical pathways implicated in the tumorigenesis and providing potential targets for therapy: the Wnt/β-catenin signaling pathway, the IGF2/IGF1R axis, and the apoptosis pathway regulated by p53. Current treatment strategies include surgical resection and mitotane, the sole adrenolytic agent approved by the FDA; however, its effects in advanced disease are suboptimal. Cytotoxic chemotherapy combined with mitotane may be applied, but survival benefits are limited so far. In the following review, we outline emerging targeted therapies, such as mTOR inhibitors and tyrosine kinase inhibitors (TKIs), which show favorable preclinical and clinical data, especially in treatment-resistant ACC. We also emphasize the possible role of immune checkpoint inhibitors (ICIs) in the management of ACC, although their effectiveness is still under study. Upcoming trends in treatment involve forms of personalized medicine, where molecular profiling is integrated to identify actionable biomarkers for administered therapies. This review will attempt to provide a comprehensive framework on how recent breakthroughs in the genomics of ACC, coupled with advances in targeted therapies and immunotherapy, can improve management.